BLS at 125: using historic principles to track the 21st-century economy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The U.S. Bureau of Labor Statistics (BLS) used its centennial in 1984 as “an opportunity to reflect on what we can learn from history and a time to think about emerging problems and their implications” for the future.1 At that time, it would have been hard to imagine the growth and change in the economy over just a quarter century—and the growth and change at the BLS designed to keep up with the changing economy. Remarkably, some things that could not have been imagined in 1984 are now commonplace at the BLS: the use of the Internet for data collection and dissemination, computers on every employee’s desk, staff telecommuting, distance training via video and computer, cognitive review to improve the clarity and accuracy of BLS questionnaires and publications, blogs and wikis, and more. But all of these changes are needed to track an economy that is increasingly global, lightning fast, and constantly being reinvented. Gone are the days when the BLS counted girdle manufacturers and stenographers. To keep up with the world of satellite communications and nanotechnology, the Agency had to reinvent itself. The 100-year anniversary was marked with the publication of a volume that traced the growth of the BLS through the terms of 10 William J. Wiatrowski is Associate Commissioner, Office of Compensation and Working Conditions, Bureau of Labor Statistics. William J. Wiatrowski BLS at 125: using historic principles to track the 21st-century economy
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it